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June 19, 2016

An improved circular consensus algorithm with an application to detect HIV-1 Drug Resistance Associated Mutations (DRAMs)

Scientists who require confident resolution of heterogeneous populations across complex regions have been unable to transition to short-read sequencing methods. They continue to depend on Sanger sequencing despite its cost and time inefficiencies. Here we present a new redesigned algorithm that allows the generation of circular consensus sequences (CCS) from individual SMRT Sequencing reads. With this new algorithm, dubbed CCS2, it is possible to reach high quality across longer insert lengths at a lower cost and higher throughput than Sanger sequencing. We applied CCS2 to the characterization of the HIV-1 K103N drug-resistance associated mutation in both clonal and patient samples.…

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April 16, 2016

Highly sensitive and cost-effective detection of somatic cancer variants using single-molecule, real-time sequencing

Next-Generation Sequencing (NGS) technologies allow for molecular profiling of cancer samples with high sensitivity and speed at reduced cost. For efficient profiling of cancer samples, it is important that the NGS methods used are not only robust, but capable of accurately detecting low-frequency somatic mutations. Single Molecule, Real-Time (SMRT) Sequencing offers several advantages, including the ability to sequence single molecules with very high accuracy (>QV40) using the circular consensus sequencing (CCS) approach. The availability of genetically defined, human genomic reference standards provides an industry standard for the development and quality control of molecular assays for studying cancer variants. Here we…

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October 7, 2015

ASHG Virtual Poster: Long range phasing of cardiac disease genes using new long read sequencing technologies

Alex Dainis, a graduate student in Euan Ashley’s lab at Stanford University, presents her ASHG 2015 poster on haplotyping for genes linked to hypertrophic cardiomyopathy. Using the Iso-Seq method with SMRT Sequencing, she sequenced full transcripts of two genes of interest, generating data on 150 different isoforms. Rare variants, which could not be found with other technologies, were associated with haplotypes.

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